Optimal control method and system for waste gas emission of cement kiln and storage medium

Abstract

The invention relates to the technical field of waste gas emission control, and discloses an optimal control method and system for waste gas emission of a cement kiln and a storage medium. The method comprises the steps that multi-point oxygen concentration data and combustion temperature data are collected in real time, and an oxygen concentration change trend is generated in combination with a prediction model; based on the oxygen concentration change trend and the combustion temperature data, a filtering algorithm is adopted to predict the temperature distribution trend in the kiln in a future period of time, whether a local high-temperature area exists or not is judged, if yes, a key airflow path in the kiln is determined according to the temperature distribution trend, an airflow retention area is recognized, and an airflow organization state analysis result is obtained; a combustion chemical reaction model is established, the sulfide generation trend is judged, and combustion atmosphere regulation and control parameters are determined; and processing regulation and control parameters by adopting a control algorithm, determining an optimal oxygen supply quantity and an optimal air distribution proportion regulation strategy, monitoring emission concentrations of nitrogen oxides and sulfides, and dynamically correcting oxygen supply and air distribution parameters. The combustion efficiency of the kiln is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of waste gas emission control, and in particular to an optimization control method and system for waste gas emission of a cement kiln and a storage medium. BACKGROUND

[0002] As the core equipment of the cement production process, the cement kiln has a complex combustion process involving high-temperature reactions, gas-solid two-phase flow and multiple chemical reactions. During operation, incomplete fuel combustion, uneven oxygen distribution and the existence of local high-temperature regions can easily lead to the generation of a large amount of pollutants such as nitrogen oxides (NOx) and sulfides (SOx), thereby causing the problem of waste gas emission exceeding the standard. Specifically, the oxygen concentration is unevenly distributed at multiple points in the kiln, and the oxygen is excessive or insufficient in some areas, affecting the completeness of fuel combustion and leading to increased energy consumption and reduced thermal efficiency. At the same time, local high-temperature regions are prone to the generation of nitrogen oxides, especially in a high-temperature and high-oxygen environment, the reaction between nitrogen and oxygen is intensified, and the emission concentration exceeds the standard; the generation of sulfides is affected by the combustion atmosphere and temperature distribution, especially in the airflow retention area, the chemical reaction is incomplete, and the risk of sulfide generation increases. In addition, improper airflow organization causes uneven heat transfer in the kiln, with overheating in some areas and insufficient temperature in other areas, affecting the product firing quality and kiln operation stability. The existing control methods for cement kilns mainly rely on single parameter adjustment, such as adjusting the primary air, secondary air ratio or changing the oxygen supply to perform extensive control, but they lack comprehensive consideration of oxygen concentration distribution, temperature field and airflow organization state. This leads to difficulties in balancing combustion efficiency, which is not conducive to pollution emission control and also causes increased energy consumption. With the increasing strictness of environmental protection requirements, it is difficult to achieve precise optimization of waste gas emission by relying on traditional experience control or simple PID control methods. Therefore, it is urgent to propose a comprehensive method combining sensor monitoring, prediction model and intelligent control algorithm to optimize the control of oxygen supply and air distribution strategy, so as to reduce waste gas emission and improve the stability and economy of system operation. SUMMARY

[0003] To solve the above technical problems, the present application provides an optimization control method and system for waste gas emission of a cement kiln and a storage medium, which are used to improve the combustion efficiency of the kiln.

[0004] In a first aspect, the present application provides an optimization control method for waste gas emission of a cement kiln, which comprises: Step S1: arranging oxygen concentration sensors and temperature sensors in multiple key regions inside the cement kiln, collecting real-time multi-point oxygen concentration data and combustion temperature data, and generating the oxygen concentration change trend of each region in the future period of time in combination with a prediction model; Step S2: based on the oxygen concentration variation trend and the combustion temperature data, a filtering algorithm is used to predict the temperature distribution trend in the kiln for a future period of time, to determine whether there is a local high-temperature area, and if so, to determine the key air flow path in the kiln according to the temperature distribution trend; Step S3: based on the key air flow path, the position information of the air flow stagnation area is identified, the state analysis result of the air flow organization is obtained, the combustion chemical reaction model is established according to the state analysis result, the sulfide generation trend is judged, and the combustion atmosphere regulation parameter is determined; Step S4: the control algorithm is used to process the regulation parameter, the optimal oxygen supply amount and air distribution ratio adjustment strategy are determined, the oxygen supply amount and air distribution system parameters of the burner are adjusted in real time according to the adjustment strategy, the concentration of nitrogen oxides and sulfides is monitored, and the oxygen supply and air distribution parameters are dynamically corrected through a closed-loop feedback mechanism.

[0005] Compared with the prior art, the beneficial effects of the present application are at least as follows: The present application can predict the future combustion condition for a period of time in advance by arranging oxygen concentration and temperature sensors in the key area of the kiln and combining support vector machine and Kalman filtering algorithm, so as to timely identify the local high-temperature area and low-oxygen area, avoid the lagging adjustment problem caused by relying on artificial experience, and realize the forward-looking control of the combustion process. Further, the fluid mechanics modeling is combined to calculate the air flow velocity field and pressure field, so as to accurately identify the key air flow path and air flow stagnation area, locate the areas with low heat transfer efficiency and oxygen utilization efficiency, and judge the sulfide generation trend by establishing a combustion chemical dynamics model, which helps to reduce the risk of incomplete combustion from the mechanism level. At the same time, the present application uses fuzzy control algorithm and multi-objective optimization method to comprehensively consider the mutual restriction relationship between the generation mechanisms of nitrogen oxides and sulfides, so as to meet the environmental protection emission standard while maintaining the combustion efficiency and economy, and avoid the deviation caused by single target adjustment. On this basis, the present application establishes a real-time closed-loop feedback mechanism, and realizes dynamic correction through the correlation comparison of emission monitoring data and oxygen supply and air distribution actions, so that the emissions of NOx and sulfides are always stable within the target control range. Compared with the existing technology which relies on fixed experience parameters or single pollutant control, the present application can realize the integrated optimization control process of prediction, analysis, control and feedback, improve the combustion efficiency and heat energy utilization rate, and ensure the long-term compliance of nitrogen oxides and sulfide emissions, which has significant energy saving and emission reduction and environmental protection benefits. BRIEF DESCRIPTION OF DRAWINGS

[0006] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0007] Figure 1 An embodiment schematic diagram of the optimization control method for the exhaust emission of the cement kiln in the embodiments of the present application; Figure 2 A flowchart for identifying the key airflow path in the kiln in the embodiments of the present application; Figure 3 A flowchart for determining the optimal oxygen supply amount and air distribution ratio adjustment strategy in the embodiments of the present application; Figure 4 An embodiment schematic diagram of the optimization control system for the exhaust emission of the cement kiln in the embodiments of the present application. DETAILED DESCRIPTION

[0008] The embodiments of the present application provide an optimization control method, system and storage medium for the exhaust emission of the cement kiln. The terms "first", "second", "third", "fourth" and the like (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the term "comprising" or "having" and any variation thereof is intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0009] For the convenience of understanding, the specific process of the embodiments of the present application will be described below. Please refer to Figure 1 An embodiment of the optimization control method for the exhaust emission of the cement kiln in the embodiments of the present application includes: Step S1: oxygen concentration sensors and temperature sensors are arranged in multiple key areas inside the cement kiln, real-time multi-point oxygen concentration data and combustion temperature data are collected, and a future oxygen concentration change trend of each area for a period of time is generated in combination with a prediction model.

[0010] Specifically, during the production process of the cement kiln, the combustion condition is complex, and the oxygen distribution and temperature field directly affect the combustion efficiency and waste gas emission level. If the oxygen supply is insufficient, it is easy to cause incomplete combustion of fuel and increase of sulfide; if the local oxygen is excessive or the temperature is too high, it will cause a large amount of nitrogen oxides (NOx) to be generated. Therefore, predicting the oxygen concentration distribution trend in the kiln is the prerequisite for optimizing the control of waste gas emission. The traditional single-point detection method cannot accurately reflect the overall situation of the kiln. The present application arranges oxygen concentration sensors and temperature sensors in multiple key areas (feed area, preheating area, burning area and cooling area, etc.) inside the cement kiln. 3-5 monitoring points are arranged in each area to form a multi-point monitoring network covering the main combustion section. The sampling frequency of the sensor is set to 1 time per second. The data is transmitted to the control unit through the industrial bus. The control unit synchronously collects the operating condition parameters of the kiln. Based on the oxygen concentration data in the historical time period and the operating condition parameters in the same time period, the prediction model is input. The future oxygen concentration change trend of each area in a period of time is output combined with the current operating condition parameters. The specific implementation process is described later. The control unit stores the predicted oxygen concentration trend as a dynamic feature library, which provides forward-looking data support for subsequent temperature field prediction and combustion optimization control.

[0011] Step S2: Based on the oxygen concentration change trend and the combustion temperature data, a filtering algorithm is used to predict the temperature distribution trend in the kiln in a future period of time, to determine whether there is a local high-temperature area. If there is, the key air flow path in the kiln is determined according to the temperature distribution trend.

[0012] Specifically, traditional temperature monitoring relies on point thermocouples, which are difficult to accurately reflect the overall three-dimensional temperature distribution of the kiln due to the limitation of point placement. Real-time collection of temperature monitoring data in each region is required for dynamic estimation of the temperature field. Therefore, the application combines the measured temperature of the sensor with the oxygen concentration trend to establish a nonlinear mapping relationship between the oxygen concentration change trend and the temperature. The Kalman filtering algorithm is used to perform the prediction and update process. First, the prior temperature distribution at the current time is predicted based on the state transition matrix. Then, the predicted value is corrected by the Kalman gain using real-time oxygen concentration observation data to obtain the posterior temperature distribution. In the prediction link, a time window of 5-15 minutes is set to consider the thermal inertia of the kiln. The future temperature distribution is calculated by multi-step recursion using the state transition equation, and the result is corrected in combination with the future trend of oxygen concentration. For example, the prediction result shows that the temperature of a certain firing zone may reach 1320℃ after 10 minutes, and the fluctuation interval is 1305-1335℃. At this time, it is determined that there is a risk of excessive generation of NOx in this region. If a high-temperature region is identified, the control unit further combines the airflow velocity field and pressure field distribution to determine the key airflow path, which refers to the main flow channel that carries a large amount of heat and oxygen and directly affects the temperature distribution and combustion efficiency. It is the main channel for transferring heat and transporting oxygen in the kiln. By identifying the key airflow path, the heat concentration area and oxygen supply main channel in the combustion process are found, so as to adjust the air volume and oxygen supply ratio in a targeted manner, making the fuel combustion more sufficient and improving the thermal efficiency.

[0013] Step S3: Identify the airflow stagnation area position information based on the key airflow path to obtain the airflow organization state analysis result, establish a combustion chemical reaction model according to the state analysis result, judge the sulfide generation trend, and determine the combustion atmosphere regulation parameter.

[0014] Specifically, in the combustion process of the cement kiln, the gas flow organization state directly determines the mixing effect of fuel and oxygen, thereby affecting the sufficiency of the combustion reaction. First, the gas flow velocity field and pressure field distribution inside the kiln are obtained based on the calculation results of fluid mechanics, and the key gas flow path information is combined to identify the gas flow stagnation area. The identification process includes: traversing the calculation grid units inside the kiln, screening out the area with a gas flow velocity lower than a set threshold, defining it as a gas flow stagnation area, further analyzing the spatial relationship between the stagnation area and the key gas flow path, identifying isolated stagnation areas away from the main flow path, and extracting the geometric feature parameters of the stagnation area, including volume, surface area, and aspect ratio, etc. Thus, the spatial coordinates, velocity parameters of the gas flow path, and the position information and geometric features of the stagnation area are integrated to form the gas flow organization state analysis results. After obtaining the gas flow organization state analysis results, a combustion chemical reaction kinetics model is further established. The model is constructed based on multi-step reaction processes such as fuel pyrolysis, volatile combustion, coke combustion, and gas phase combustion, the mixing degree coefficient of fuel and oxygen is determined combining the gas flow velocity field and turbulence intensity parameters, and the effective reaction volume and residence time in the reaction area are corrected using the pressure field distribution. Through the model, the main reaction zone and the secondary reaction zone can be identified, where the main reaction zone is an area with sufficient oxygen supply and sufficient flow mixing, and the secondary reaction zone is an area with insufficient oxygen and gas flow stagnation. When solving the reaction kinetics model, the actual oxygen concentration distribution of each area is calculated and compared with the theoretical oxygen concentration required for complete fuel combustion. When the actual oxygen concentration is lower than the theoretical value, it is judged that there is a trend of increased sulfide generation in this area. On this basis, by analyzing the reaction path and generation rate of sulfide generation, the strength and development direction of the sulfide generation trend are identified. Finally, according to the sulfide generation trend, the specific parameter requirements of the combustion atmosphere regulation are determined, including the oxygen concentration supplement, the burner air distribution adjustment scheme, and the distribution strategy of different air ducts. Through dynamic calculation of the matching relationship between the oxygen concentration difference and the air distribution capacity, the adjustment parameters for combustion control are generated, thereby realizing effective inhibition of sulfide generation and optimization of the combustion atmosphere. By combining gas flow stagnation area identification and combustion kinetics modeling, the sulfide generation trend can be accurately judged, and the corresponding regulation parameters are given, providing reliable support for precise control of kiln exhaust gas emission.

[0015] Step S4: processing the regulation parameters using a control algorithm to determine the optimal oxygen supply amount and air distribution adjustment strategy, adjusting the oxygen supply amount and air distribution system parameters of the burner in real time according to the adjustment strategy, monitoring the concentrations of nitrogen oxides and sulfides, and dynamically correcting the oxygen supply and air distribution parameters through a closed-loop feedback mechanism.

[0016] Specifically, the combustion atmosphere regulation parameter requirements output by the combustion chemical reaction kinetics model are acquired, the parameter requirements including oxygen concentration threshold, temperature distribution index, and airflow organization state information, a fuzzy control algorithm is used to establish a fuzzy relationship matrix of nitrogen oxide generation amount and oxygen concentration, and a sulfur compound generation amount and oxygen concentration, a constraint relationship rule base of the two is constructed, a pollution generation trend under different working conditions is analyzed through fuzzy reasoning, an initial value of oxygen supply amount adjustment is obtained through gravity method solution defuzzification processing, a multi-objective optimization method is used to balance among three objectives of minimizing nitrogen oxide emission concentration, minimizing sulfur compound emission concentration, and maximizing combustion efficiency, a constraint condition is constructed and an optimal oxygen supply amount is solved. Based on the optimal solution, the oxygen distribution amount of the burner and the proportional distribution of the primary air, the secondary air, and the tertiary air are calculated in combination with the combustion requirements of each region of the kiln, a proportion adjustment strategy of air distribution is generated, thereby forming a combustion optimization control parameter. In the control execution process, the control unit adjusts the oxygen supply amount and the air distribution system parameter of each burner in real time according to the adjustment strategy, and collects the emission concentration data of nitrogen oxide and sulfur compound in real time through the multi-point monitoring device. After the monitoring data are preprocessed and trend analyzed, the data are compared with the control target range. When the detection result exceeds the preset standard, a closed-loop feedback mechanism is triggered. According to the deviation degree and trend direction of the emission concentration, the oxygen supply amount and the air distribution proportion distribution strategy are dynamically corrected, the iteration optimization of the combustion parameter is realized, and it is ensured that the nitrogen oxide and sulfur compound emissions are always maintained within the target control range. In complex working conditions, the combustion process is accurately controlled under the coupling of multiple parameters, the fuel combustion efficiency is ensured, the pollution emission is effectively reduced, and the energy saving and environmental protection performance of the cement kiln is significantly improved.

[0017] In a specific embodiment, generating the oxygen concentration change trend of each region in the future period of time in combination with the prediction model specifically includes the following steps: The historical oxygen concentration data and the historical working condition parameters of multiple points inside the kiln are acquired, the collected historical oxygen concentration data are preprocessed, a support vector machine algorithm is used to establish a prediction model, the historical oxygen concentration data and the historical working condition parameters are input into the prediction model as training data, a nonlinear mapping relationship between the working condition parameters and the oxygen concentration is established, the current working condition parameters are input into the prediction model, the oxygen concentration distribution trend and fluctuation range of each region in the future are obtained, and the dynamic change characteristics of the oxygen concentration of each region are determined according to the concentration fluctuation range.

[0018] Specifically, first, oxygen concentration sensors are arranged at key positions of the kiln to form a multi-point monitoring network, and kiln operating condition parameters are synchronously collected, including fuel supply amount, combustion air flow, kiln speed, material feeding speed, and regional temperature, etc. The collected historical oxygen concentration data are preprocessed, including outlier rejection, missing value filling, and data standardization. Through this step, sensor noise and dimension difference can be eliminated to ensure the reliability and consistency of input data. Then, the operating condition parameters are taken as input feature vectors, and the oxygen concentration at the corresponding time is taken as output label to construct the training sample set of the support vector machine, i.e., the prediction model. The support vector machine model is a classification and regression algorithm based on statistical learning theory, which is suitable for small sample, high dimension, and nonlinear problems, and is particularly suitable for the complex multi-factor coupling scene in kiln combustion. In the modeling process, the radial basis function (RBF) is selected as the kernel function, and the optimal kernel parameter and penalty parameter are determined through cross-validation to balance the model complexity and prediction accuracy. The gradient descent method is used to train the model to gradually optimize the distribution of support vectors and the decision boundary, and to establish the nonlinear mapping relationship between the operating condition parameters and the oxygen concentration. After training, the oxygen concentration variation prediction model is obtained. This model can quickly respond to the input of the current operating condition parameters and output the future prediction value in real-time operation. In the prediction stage, the current operating condition parameters are input into the trained support vector machine prediction model to calculate the oxygen concentration prediction value of each region in the future time period. The prediction time window can be set to 30 minutes in the future, and multiple prediction points can be obtained at intervals of 5 minutes to form a continuous prediction curve. Through linear regression fitting of the prediction value, the oxygen concentration distribution trend of each region is obtained to reflect the direction and rate of change of the oxygen concentration with time. Meanwhile, the standard deviation and coefficient of variation of the prediction value are calculated to form the confidence interval of the oxygen concentration, which is used to determine the concentration fluctuation range. This fluctuation range provides a safety margin for combustion control to avoid the deviation of oxygen concentration from the reasonable range.

[0019] Further, through statistical analysis of the prediction results, the dynamic change characteristics of different regions can be identified. The regions with larger fluctuation range are usually located near the burner, with fast oxygen consumption speed and frequent concentration change, and should be the key control objects. The regions with smaller fluctuation range indicate stable combustion. By comparing the variation coefficients of different regions, the kiln can be divided into high fluctuation zone, medium fluctuation zone, and low fluctuation zone. The periodic variation characteristics of oxygen concentration can be extracted and obtained through Fourier transform to reflect the influence of fuel supply period or material feeding period on oxygen concentration, providing decision basis for time sequence air regulation of the burner. Finally, a dynamic change characteristic library of oxygen concentration is established to archive parameters such as concentration change amplitude, change rate, periodic characteristics, and regional differences of each region under different operating conditions. The characteristic library can be continuously updated and improved to provide important data support for subsequent combustion chemical reaction modeling, temperature distribution prediction, and pollutant emission control.

[0020] In a specific embodiment, the step of predicting the temperature distribution trend in the kiln in a future period of time using a filtering algorithm comprises the following steps: A state space model of the temperature distribution in the kiln is established, the temperature values of each monitoring point in the kiln are taken as state variables, a state transition matrix is constructed, the parameters of the state transition matrix are determined based on statistical analysis of historical temperature data, a dynamic relationship between the temperature distribution at the current time and the temperature distribution at the previous time is established, and process noise is introduced; The temperature distribution state at the previous time is predicted based on the state transition matrix to obtain an a priori temperature distribution estimate at the current time, the a priori temperature distribution estimate is corrected through a Kalman gain matrix to obtain a posterior current temperature distribution state; The current temperature distribution state is taken as an initial condition, the state transition matrix is used for multi-step prediction to obtain temperature distribution prediction results at future times, the temperature distribution prediction results are corrected in combination with the oxygen concentration change trend to obtain the temperature distribution trend in a future period of time.

[0021] Specifically, firstly, a state space model of the kiln temperature distribution is established, the temperature values of each monitoring point in the kiln are set as state variables, a state transition matrix is constructed to represent the evolution law of temperature with time, and the matrix parameters are determined through statistical analysis of historical temperature data, and process noise is introduced to describe the uncertainty such as fuel fluctuation and air flow disturbance. For example, in a certain rotary kiln, the thermal conductivity coefficient of adjacent regions in the kiln is 0.15 and the heat capacity parameter is 0.8, which are calculated based on six months of operation data, thereby forming a state equation for reflecting the dynamic relationship between the kiln at different times. Secondly, an observation equation is established, which represents the corresponding relationship between the oxygen concentration distribution trend data and the temperature state variables. The stoichiometric relationship of the combustion reaction is used to map the oxygen consumption rate and the temperature rise, for example, when the oxygen concentration in a certain region decreases from 21% to 15%, the temperature rise is estimated to be about 85°C, and a measurement noise factor is introduced in the observation equation to cope with the error interference of sensor accuracy. Then the Kalman filtering process is performed, firstly, the prior temperature distribution estimation at the current time is obtained by using the state transition matrix, and then the prior result is corrected by Kalman gain combined with the observation data of oxygen concentration to obtain the posterior temperature distribution state, for example, the prior estimated temperature is 1250°C at a certain time, and the corrected temperature is 1245°C, which effectively reduces the prediction error of 5°C. Subsequently, the corrected temperature state is used as the initial condition, and the state transition matrix is used for multi-step prediction. In the case of setting the prediction time window to 10 minutes, the temperature distribution result is output once a minute, for example, in the next 5 minutes, the predicted temperature rises from 1245°C to 1290°C, and the reliability in the prediction interval is evaluated by the covariance matrix. When combined with the future downward trend of oxygen concentration, if the oxygen concentration is expected to decrease by 2%, the predicted temperature curve will be adjusted downward by about 20°C to better conform to the actual combustion trend. Finally, the predicted temperature distribution is scanned, if the local temperature exceeds the threshold of 1300°C and lasts for several prediction steps, it is determined that there is a risk of excessive generation of nitrogen oxides in this region, and the temperature optimization target parameters are determined, including the target temperature not exceeding 1280°C, the temperature uniformity index controlled to a variance of less than 15, and the temperature gradient controlled to not more than 100°C / m, thereby providing a basis for subsequent air flow path identification and combustion optimization control.

[0022] In a specific embodiment, determining the key air flow path in the kiln according to the temperature distribution trend specifically includes the following steps: A three-dimensional geometric model of the interior of the kiln is established, the three-dimensional geometric model is divided into a plurality of grid elements, and a fluid mechanics calculation method is used to calculate the air flow velocity field distribution in the kiln; Based on the air flow velocity field distribution, the pressure value of each grid element is solved by the pressure correction equation, the pressure field distribution characteristics in the kiln are obtained, based on the air flow velocity field distribution, the velocity value of all grid elements is traversed, the grid elements with velocity greater than the preset threshold value are screened out, and the high-speed airflow channel is generated by connecting the grid elements; The pressure difference between adjacent grid elements is calculated to obtain the pressure gradient distribution characteristics, and the grid area with pressure gradient greater than the preset threshold value is identified as the strong driving force area; The airflow path of the high-speed airflow channel and the strong driving force area is superimposed and analyzed with the temperature distribution, and the airflow path that meets the conditions of high-speed flow and high temperature difference at the same time is identified as the key airflow path.

[0023] Specifically, as Figure 2The flowchart for identifying the key airflow path in the kiln is shown, a three-dimensional geometric model of the kiln consistent with the actual working condition is established, and the kiln body, burner nozzle, material layer and flue area are modeled. The model is divided into a plurality of calculation grid units, among which the burner vicinity and high temperature gradient area adopt encrypted grid to ensure simulation accuracy and numerical stability. Subsequently, the boundary conditions and physical parameters are set, the burner outlet is defined as a velocity inlet, the kiln tail is set as a pressure outlet, the inner wall is set as a non-slip isothermal wall, and the Reynolds averaged Navier-Stokes (RANS) equation set is coupled with the energy equation for numerical solution. The velocity field distribution in the kiln is obtained by discrete finite volume method and SIMPLE algorithm iteration. At the same time, the pressure of each grid unit is solved based on the continuity correction equation to form the pressure field distribution consistent with the velocity field. After obtaining the velocity field, the velocity values of each grid unit are screened, the calculation domain is traversed and the units with velocity greater than 1.5 times the average velocity are extracted, which are connected into high-speed airflow channels through connectivity clustering algorithm. In order to avoid the interference of false local high flow velocity points, the candidate channels are further subjected to streamline tracking and geometric smoothing treatment to extract high-speed main channels with good continuity. At the same time, the pressure gradient distribution field is obtained by calculating the pressure difference between adjacent grid units and dividing by the center distance, and the connected area with a pressure greater than a predetermined threshold (for example, 500 Pa / m) is marked as a strong driving force area to represent the airflow path mainly driven by pressure difference. On this basis, the temperature field data is interpolated to the center line of the candidate channel, and the average temperature difference of adjacent sections along the line is calculated. When the channel meets the two conditions of "high-speed flow" (average velocity ≥ 5 m / s or ≥ 1.5 times the global average) and "high temperature difference" (average temperature difference along the line ≥ 100°C or located in the predicted high temperature gradient area), and the channel path overlaps or is tangent to at least one strong driving force area, the channel is defined as a key airflow path. Finally, the geometric and physical characteristic parameters of the key airflow path are output, including the start and end coordinates, length, average / peak velocity, average temperature difference along the line, proportion of passing through the pressure gradient area, and minimum distance from the material layer or kiln wall, etc. Through the above method, the real airflow channel that plays a major role in the complex flow field inside the kiln can be quickly identified, that is, the "main channel" that can not only take away heat but also send oxygen to the combustion area. In this way, the operator can clearly know which areas are the main paths of heat and oxygen transfer, and which areas are prone to dead angles and stagnation. Based on this identification result, subsequent air distribution and oxygen supply adjustment can be targeted to send air or oxygen to the key channel, avoiding local overheating or oxygen-deficient combustion problems, thereby reducing the emission of nitrogen oxides and sulfides, and ensuring that the material can be uniformly and fully calcined.

[0024] In a specific embodiment, the key airflow path is used to identify the position information of the airflow stagnation area, and the airflow organization state analysis result includes the following steps: By traversing all grid cells within the kiln, grid regions with airflow velocities below a preset threshold are selected and defined as airflow stagnation regions. The geometric characteristic parameters of the airflow stagnation regions are determined, including the volume, surface area, and aspect ratio of each stagnation region. The airflow velocity field distribution data, pressure field distribution characteristics, key airflow path information, stagnation region location information, and geometric characteristics inside the kiln are integrated to form the airflow organization state analysis results.

[0025] Specifically, the entire kiln grid is traversed one by one, the scalar velocity of each cell is calculated, and compared with a preset threshold (e.g., 0.3 times the average velocity) determined based on the overall average velocity. Connected cells with velocities below the threshold are marked as airflow stagnation regions. For each stagnation region, its geometric and topological features are further extracted: the volume and surface area are calculated based on the cumulative accumulation of grid volume and surface area, the outer envelope is fitted along the principal inertial axis to obtain the three-dimensional scale of length, width, and thickness, and the aspect ratio is calculated accordingly. At the same time, the geometric center, centroid, and boundary point data of the region are generated. Subsequently, the spatial relationship between the stagnation region and the critical airflow path is analyzed, the minimum spatial distance from the geometric center of the stagnation region to the centerline of the nearest critical airflow path is calculated, and the coupling degree with the mainstream region is determined by combining the path tangential velocity and local pressure gradient: among them, regions with larger distances and weaker coupling are defined as isolated stagnation regions, usually located in the corners or dead corners of the kiln, with insufficient heat and oxygen exchange; while regions adjacent to or tangential to the critical path are defined as accompanying stagnation regions, which, although partially affected by mainstream disturbances, still have the risk of local incomplete combustion. Simultaneously, based on the pressure field distribution, the pressure gradient and curl at the boundary of the stagnation zone are statistically analyzed to assess its internal circulation intensity and heat accumulation trend. Finally, the spatial location, geometric scale, relationship with the mainstream path, and statistical characteristics of velocity and pressure within the stagnation zone are integrated with the coordinates and flow characteristic parameters (including path length, average velocity, and proportion of high-temperature zones traversed) of key airflow paths to form the airflow organization state analysis results. These results not only visually reflect the dominant heat transfer and oxygen supply channels within the kiln but also identify potential combustion weakness zones, providing direct input for subsequent zonal modeling and air distribution control in combustion reaction kinetics.

[0026] In one specific embodiment, establishing a combustion chemical reaction model based on the state analysis results and determining the sulfide formation trend specifically includes the following steps: The oxygen concentration, fuel concentration, and product concentration parameters are extracted from the state analysis results and substituted into the reaction kinetic equations to calculate the actual oxygen concentration distribution. Obtain the minimum theoretical oxygen concentration required for complete combustion of fuel. If the actual oxygen concentration is lower than the minimum theoretical oxygen concentration, it is determined that there is an increasing trend of sulfide formation in the region. Based on the sulfide formation trend, determine the specific parameter requirements for combustion atmosphere control.

[0027] Specifically, the gas flow organization state analysis result is obtained, which contains the gas flow velocity field distribution data, pressure field distribution characteristics, key gas flow path coordinates, and residence area position information inside the kiln; secondly, a fuel combustion chemical reaction kinetics model is established based on the above data, the model divides different regions in the kiln into functions, the high-speed flow region is set as the main reaction zone, in which the oxygen supply is sufficient, and the fuel mainly undergoes complete oxidation reaction, and the side reaction zone corresponds to the residence area, which is prone to cause fuel pyrolysis or incomplete combustion due to low gas flow velocity and poor oxygen transfer efficiency, thereby promoting the generation of reducing sulfides; thirdly, a multi-step kinetic equation set including fuel pyrolysis, volatile combustion, coke combustion, and gas phase combustion is constructed, and the Arrhenius equation is used to describe the reaction rate, and the pressure field correction factor is used to correct the gas density change, so that the model can more truly reflect the reaction process under actual working conditions. In the kinetic model, the theoretical minimum oxygen concentration required for complete combustion of fuel is calculated by inputting the fuel element analysis result (such as the mass fraction of carbon, hydrogen, and sulfur), and further compared with the actual oxygen concentration in the reaction zone. When the actual concentration is lower than the theoretical value, it is determined that there is an increasing trend of sulfide generation in the region. For example, in the middle residence area of a certain rotary kiln, the calculated theoretical minimum oxygen concentration is 12%, and the actually measured concentration is only 8.5%, which is about 70.8% of the theoretical value, far below the level required for complete combustion, and thus it is identified as a region with serious oxygen deficiency. Under this condition, the model calculates that the sulfur element in the fuel preferentially combines with hydrogen to generate hydrogen sulfide, and the generation rate can reach 0.15 mg / s·m³, which is more than 3 times higher than that under the complete combustion condition; when hydrogen is almost consumed, the sulfur element further combines with carbon to generate carbon disulfide, and the generation process requires higher temperature, which further increases the risk of local pollutant generation. Based on the above results, the system determines the specific parameter requirements of the combustion atmosphere regulation according to the sulfide generation trend. For example, when it is calculated that the oxygen concentration needs to be supplemented by 4.2 percentage points, the control unit generates a corresponding air distribution adjustment scheme, increases the air distribution ratio of the burner in a certain region from 65% to 78%, and increases the secondary air ratio from 35% to 42%, so as to ensure that the oxygen concentration in the residence area is restored to above the theoretical value, thereby effectively inhibiting the further generation of sulfides. Through the above method, the high-risk areas of sulfide generation can be accurately predicted and identified under complex working conditions, and they are converted into quantifiable oxygen supplement amount and air distribution ratio regulation parameters, which not only improves the accuracy of the combustion reaction modeling, but also significantly enhances the foresight and effectiveness of the emission control.

[0028] In a specific embodiment, the control algorithm is used to process the regulation parameters to determine the optimal oxygen supply amount and air distribution ratio adjustment strategy, which specifically includes the following steps: Based on the parameter demand of combustion atmosphere regulation, the fuzzy relationship matrix of nitrogen oxides and sulfide generation with oxygen concentration change was established, and the mutual restraint relationship fuzzy rule base of nitrogen oxides and sulfide generation mechanism was constructed; The pollutant generation trend under different working conditions was analyzed by using fuzzy reasoning process, and the fuzzy reasoning result was de-fuzzied by using gravity method, to obtain the oxygen supply adjustment value; A multi-objective optimization function was constructed with the adjustment value as the core variable, and the optimal oxygen supply amount was determined under the constraints of emission concentration, combustion efficiency and operation economy; Based on the optimal oxygen supply amount, combined with the combustion demand of each region in the kiln, the air distribution proportion adjustment strategy of the burner was calculated, and the combustion optimization control parameters were obtained.

[0029] Specifically, as Figure 3The flow chart for determining the optimal oxygen supply and air distribution adjustment strategy is shown. First, based on the oxygen concentration threshold, temperature distribution characteristics and airflow organization state data extracted from the combustion atmosphere regulation parameter requirements as input conditions, a fuzzy relationship matrix of nitrogen oxide and sulfide generation with oxygen concentration is established. Oxygen concentration is divided into low concentration (6%-10%), medium concentration (10%-14%) and high concentration (14%-18%) three fuzzy sets, and triangular membership function is used to describe the fuzzy boundary. For example, when the oxygen volume fraction is 12%, the membership degree of medium concentration set is 1.0, and the membership degrees of low and high concentration sets are 0. At the same time, the sulfide generation is divided into low generation, medium generation and high generation three fuzzy sets, and the corresponding membership function is determined by combining historical operation data of the kiln and calculation results of combustion kinetics. Based on the above fuzzy sets, a fuzzy rule base of mutual restraint relationship of nitrogen oxide and sulfide generation mechanism is established, which contains 27 reasoning rules. For example, when the oxygen concentration is high and the combustion temperature is 1400℃, the nitrogen oxide generation is inferred to be high, while the sulfide generation is inferred to be low. On the contrary, when the oxygen concentration is 8% and the combustion temperature is 1250℃, the nitrogen oxide generation is low, while the sulfide generation is high. Through the rule base, the balance judgment of the generation trend of the two types of pollutants can be realized. In the fuzzy reasoning process, the rule base is combined with the working condition parameter input of different regions to obtain the fuzzy output result, and the gravity method is used for defuzzification to obtain the specific oxygen supply adjustment value. For example, when the fuzzy results of a certain region reasoning output correspond to oxygen supply of 10%, 12% and 14% respectively, and the membership degrees are 0.2, 0.5 and 0.3 respectively, the final supply obtained by the gravity method is 12.2%. This value is used as the core variable for subsequent optimization calculation. A multi-objective optimization function is established to determine the optimal oxygen supply, and the optimization objectives include: ① minimizing the nitrogen oxide emission concentration, with the constraint condition that NOx emission shall not exceed 200mg / m³; ② minimizing the sulfide emission concentration, with the constraint condition that the sulfide emission concentration shall not exceed 50mg / m³; ③ maximizing the fuel combustion efficiency, with the target efficiency set not less than 94%, and the constraint condition further limiting the oxygen supply range to 0.8 times to 1.3 times of the stoichiometric ratio, and the air distribution ratio difference of the burner shall not exceed 15%. Non-dominated sorting genetic algorithm (NSGA-II) is used for solution, and the algorithm parameters include population size 100, evolution algebra 200, crossover probability 0.9 and mutation probability 0.1. A series of Pareto optimal solutions are obtained, for example, solution A corresponds to NOx emission concentration of 180mg / m³, sulfide emission concentration of 48mg / m³ and combustion efficiency of 94.5%; solution B corresponds to NOx emission concentration of 200mg / m³, sulfide emission concentration of 40mg / m³ and combustion efficiency of 95.0%.According to the actual environmental protection policy requirements and economic demand, if the emission standard is the priority target, solution A is selected as the optimal supply amount scheme. Finally, based on the selected optimal oxygen supply amount, combined with the combustion intensity and temperature distribution of each region of the kiln, the air distribution proportion adjustment strategy of the burner is calculated. Assuming that the total oxygen demand of the kiln is determined to be 1.15 times the stoichiometric ratio after optimization, the air distribution proportion of the main burner can be set to primary air 25%, secondary air 45%, and tertiary air 30%, and the auxiliary burner is adjusted according to the regional demand to ensure balanced oxygen distribution, which meets the requirements of combustion efficiency and controls the pollutant emission level. Through this implementation mode, the nitrogen oxide and sulfur oxide emission control can be considered under complex combustion conditions, and the combustion efficiency can be improved.

[0030] In a specific embodiment, the real-time regulation of the oxygen supply amount and the air distribution system parameters of the burner according to the adjustment strategy and the monitoring of the nitrogen oxide and sulfur oxide emission concentration specifically include the following steps: Obtain the oxygen supply amount and the air distribution proportion adjustment strategy from the combustion optimization control parameters, and convert them into adjustment instructions; Based on the adjustment instructions, real-time adjust the oxygen supply amount of each burner, and simultaneously correct the air distribution system parameters; After the execution of the adjusted parameters, real-time collect and trend analyze the nitrogen oxide and sulfur oxide emission concentration to obtain the emission concentration data; Correlate and compare the emission concentration data with the oxygen supply and air distribution adjustment actions of the burner to determine whether the emission result meets the target control range; If the emission concentration exceeds the target range, trigger the feedback correction mechanism to dynamically adjust the oxygen supply amount and the air distribution parameters of the burner until the target control range is met.

[0031] Specifically, first, in the kiln calcination working condition, due to the fluctuation of fuel composition and heat load, the traditional fixed air distribution mode cannot balance the combustion efficiency and pollutant emission control, which is easy to cause excessive generation of nitrogen oxides or excessive emission of sulfides. Therefore, the control unit needs to convert the oxygen supply amount and air distribution proportion adjustment strategy into executable adjustment instructions based on the combustion optimization control parameters obtained in the previous step, and issue them to each burner and air distribution execution mechanism. Specifically, assuming that the kiln is equipped with 12 burners, including 4 main burners, 6 auxiliary burners and 2 compensation burners, when the optimization control parameters give that the oxygen concentration in a certain area needs to be increased by 2.5 percentage points, the control unit will increase the oxygen supply amount of the main burner in this area from the original setting of 800 Nm³ / h to 880 Nm³ / h (an increase of 10%), while the oxygen supply amount of the adjacent two auxiliary burners will be increased from 600 Nm³ / h to 630 Nm³ / h (an increase of 5%), so as to realize regional oxygen enrichment. Secondly, the control unit adjusts the oxygen supply amount of each burner in real time based on the adjustment instructions, and synchronously corrects the air distribution system parameters. The air distribution system includes three subsystems: primary air, secondary air and tertiary air. The primary air is used for fuel ignition, the secondary air is used for main combustion process, and the tertiary air is used for burnout and temperature regulation. When the oxygen supply amount of the main burner is increased to 880 Nm³ / h, the system automatically increases the secondary air flow in this area from 1200 Nm³ / h to 1320 Nm³ / h, with an increase of about 10%, while the tertiary air is slightly reduced by 5%, from 800 Nm³ / h to 760 Nm³ / h, to avoid excessive generation of NOx in high temperature area, and the primary air remains stable at 95% of the design value, to ensure the stability of the flame. After the adjustment is completed, the system collects and analyzes the trend of the emission concentrations of nitrogen oxides and sulfides in real time to obtain the emission concentration data. A multi-point gas monitoring device is arranged at the outlet of the kiln. NOx is determined by chemiluminescence method, with an accuracy of 1 ppm and a response time of 3 s; sulfides are determined by ultraviolet fluorescence method, with an accuracy of 0.5 ppm and a response time of 5 s. For example, after the above adjustment is executed for 10 minutes, the monitoring data shows that the NOx concentration increases from 190 ppm before adjustment to 198 ppm, which is still within the control target range of 150-200 ppm, while the sulfide concentration decreases from 78 ppm to 66 ppm, which is obviously improved.Further, the control unit associates and compares the emission concentration data with the oxygen supply and air distribution adjustment actions of the burner to determine whether the emission results meet the target control range. When it is found that the NOx concentration exceeds the upper limit of the target or the sulfide concentration is lower than the lower limit of the target, the system triggers a feedback correction mechanism. For example, when the temperature of the third control area exceeds 1250 DEG C and the NOx concentration rises to 220 ppm, the system determines that the NOx in the area exceeds the standard, and then adjusts the oxygen supply of the main burner from 950 Nm 3 / h to 855 Nm 3 / h (a decrease of 10%), and at the same time, adjusts the tertiary air from 820 Nm 3 / h to 740 Nm 3 / h (a decrease of about 10%). After the adjustment, the NOx concentration decreases to 185 ppm within 15 minutes and returns to the target range. Finally, when the sulfide emission exceeds the standard, the feedback correction mechanism preferentially increases the oxygen supply of the local low-oxygen area. For example, when the sulfide concentration of the first control area reaches 92 ppm, which exceeds the upper limit of the target by 80 ppm, the system immediately starts the compensation burner and supplies oxygen at a rate of 400 Nm 3 / h, and at the same time, the auxiliary burner is increased from 700 Nm 3 / h to 770 Nm 3 / h (an increase of 10%), and the secondary air is increased from 1000 Nm 3 / h to 1150 Nm 3 / h. After the adjustment is completed, the sulfide concentration decreases to 70 ppm within 20 minutes, achieving effective control. Through the above implementation, real-time dynamic adjustment of the oxygen supply and air distribution parameters of the burner can be realized under complex combustion conditions, and the closed-loop feedback mechanism is used to ensure that the nitrogen oxides and sulfides are always maintained within the preset target range, thereby improving the stability of the combustion process and the environmental protection compliance rate, and avoiding the increase of energy consumption caused by excessive adjustment.

[0032] The above describes a method for optimizing control of cement kiln exhaust emission according to an embodiment of the present application. Next, a system for optimizing control of cement kiln exhaust emission according to an embodiment of the present application is described. Please refer to Figure 4 A system for optimizing control of cement kiln exhaust emission according to an embodiment of the present application includes: A collection module, oxygen concentration sensors and temperature sensors are arranged in multiple key areas inside the cement kiln, real-time collection of multi-point oxygen concentration data and combustion temperature data is performed, and a future oxygen concentration trend of each area is generated in combination with a prediction model; A prediction module, based on the oxygen concentration trend and the combustion temperature data, a temperature distribution trend in the kiln in a future period of time is predicted by using a filtering algorithm, whether there is a local high-temperature area is determined, and if there is, a key air flow path in the kiln is determined according to the temperature distribution trend; A state analysis module, based on the key air flow path, position information of an air flow stagnation area is identified, a state analysis result of air flow organization is obtained, a combustion chemical reaction model is established according to the state analysis result, a sulfide generation trend is determined, and a combustion atmosphere regulation parameter is determined; The adjusting module adopts a control algorithm to process the regulation parameters, determines an optimal oxygen supply amount and air distribution ratio regulation strategy, regulates the oxygen supply amount of the burner and the air distribution system parameters in real time according to the regulation strategy, monitors the concentration of nitrogen oxide and sulfide emissions, and dynamically corrects the oxygen supply and air distribution parameters through a closed-loop feedback mechanism.

[0033] The application further provides a computer readable storage medium, which can be a non-volatile computer readable storage medium or a volatile computer readable storage medium, and instructions are stored in the computer readable storage medium, and when the instructions are run on a computer, the computer is caused to execute the steps of the method for optimizing control of cement kiln exhaust emission.

[0034] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, system and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0035] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the application. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0036] The above-described embodiments are only used to illustrate the technical solutions of the application, rather than limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the application.

Claims

1. A method for optimized control of cement kiln exhaust gas emissions, characterized in that, The method comprises: Step S1: arranging oxygen concentration sensors and temperature sensors in multiple key areas inside the cement kiln, collecting real-time multi-point oxygen concentration data and combustion temperature data, and generating oxygen concentration change trends of each area in a future period of time in combination with a prediction model; Step S2: predicting temperature distribution trends in the kiln in a future period of time based on the oxygen concentration change trends and the combustion temperature data, using a filtering algorithm to determine whether there is a local high-temperature area, and if so, determining a key air flow path in the kiln according to the temperature distribution trends; Step S3: identifying air flow stagnation area position information based on the key air flow path, obtaining air flow organization state analysis results, establishing a combustion chemical reaction model according to the state analysis results, judging a sulfide generation trend, and determining combustion atmosphere regulation parameters; Step S4: processing the regulation parameters using a control algorithm to determine an optimal oxygen supply amount and air distribution ratio adjustment strategy, real-time regulating oxygen supply amount and air distribution system parameters of the burner according to the adjustment strategy, monitoring nitrogen oxide and sulfide emission concentrations, and dynamically correcting oxygen supply and air distribution parameters through a closed-loop feedback mechanism.

2. The method of claim 1, wherein, Generating oxygen concentration change trends of each area in a future period of time in combination with a prediction model comprises: obtaining historical oxygen concentration data and historical working condition parameters of multiple points inside the kiln, preprocessing the collected historical oxygen concentration data, establishing a prediction model using a support vector machine algorithm, inputting the historical oxygen concentration data and the historical working condition parameters into the prediction model as training data, establishing a nonlinear mapping relationship between the working condition parameters and the oxygen concentration, inputting the current working condition parameters into the prediction model, obtaining oxygen concentration distribution trends and fluctuation ranges of each area in the future, and determining dynamic change characteristics of the oxygen concentration of each area according to the concentration fluctuation range.

3. The method of claim 1, wherein, Predicting temperature distribution trends in the kiln in a future period of time using a filtering algorithm comprises: establishing a state space model of the kiln temperature distribution, taking temperature values of each monitoring point in the kiln as state variables, constructing a state transition matrix, determining parameters of the state transition matrix based on statistical analysis of historical temperature data, establishing a dynamic relationship between the current temperature distribution and the previous temperature distribution, and introducing process noise; predicting the temperature distribution state of the previous time based on the state transition matrix to obtain a prior temperature distribution estimate of the current time, correcting the prior temperature distribution estimate through a Kalman gain matrix to obtain a posterior current temperature distribution state; using the current temperature distribution state as an initial condition, performing multi-step prediction using the state transition matrix to obtain temperature distribution prediction results at future times, correcting the temperature distribution prediction results in combination with the oxygen concentration change trends to obtain temperature distribution trends in a future period of time.

4. The method of claim 1, wherein, Determining a key air flow path in the kiln according to the temperature distribution trends comprises: establishing a three-dimensional geometric model of the kiln, dividing the three-dimensional geometric model into multiple grid elements, and calculating air flow velocity field distribution in the kiln using a fluid mechanics calculation method; Based on the air flow velocity field distribution, the pressure value of each grid element is solved by the pressure correction equation to obtain the pressure field distribution characteristics in the kiln. Based on the air flow velocity field distribution, the velocity value of all grid elements is traversed, and the grid elements with a velocity greater than a preset threshold value are selected to generate a high-speed air flow channel by connecting the grid elements. The pressure difference between adjacent grid elements is calculated to obtain the pressure gradient distribution characteristics, and the grid area with a pressure gradient greater than a preset threshold value is identified as a strong driving force area. The high-speed air flow channel and the air flow path of the strong driving force area are superimposed and analyzed with the temperature distribution to identify the air flow path that meets the conditions of high-speed flow and high temperature difference, which is defined as the key air flow path.

5. The method of claim 1, wherein, Based on the key air flow path, the position information of the air flow stagnation area is identified to obtain the air flow organization state analysis result, including: Traverse all grid elements in the kiln, select the grid area with air flow velocity less than a preset threshold value, define it as an air flow stagnation area, determine the geometric characteristic parameters of the air flow stagnation area, including the volume, surface area and aspect ratio of each stagnation area, integrate the air flow velocity field distribution data, pressure field distribution characteristics, key air flow path information, stagnation area position information and geometric characteristics to form the air flow organization state analysis result.

6. The method of claim 5, wherein, According to the state analysis result, a combustion chemical reaction model is established to judge the sulfide generation trend, including: Extract oxygen concentration, fuel concentration and product concentration parameters from the state analysis result and substitute them into the reaction kinetics equation set to calculate the actual oxygen concentration distribution; Obtain the theoretical minimum oxygen concentration required for complete combustion of fuel, if the actual oxygen concentration is lower than the theoretical minimum oxygen concentration, it is judged that there is an increasing trend of sulfide generation in this area; According to the sulfide generation trend, determine the specific parameter demand of combustion atmosphere regulation.

7. The method of claim 1, wherein, Use control algorithm to process the regulation parameters to determine the optimal oxygen supply amount and air distribution ratio adjustment strategy, including: Based on the parameter demand of combustion atmosphere regulation, establish a fuzzy relationship matrix of nitrogen oxide and sulfide generation amount with oxygen concentration change, and construct a fuzzy rule base of the mutual restriction relationship of nitrogen oxide and sulfide generation mechanism; Use fuzzy reasoning process to analyze the pollutant generation trend under different working conditions, and use the gravity method to de-fuzzify the fuzzy reasoning result to obtain the oxygen supply amount adjustment value; Take the adjustment value as the core variable to construct a multi-objective optimization function, and determine the optimal oxygen supply amount under the constraints of emission concentration, combustion efficiency and operation economy; Based on the optimal oxygen supply amount, calculate the burner air distribution ratio adjustment strategy combined with the combustion demand of each area in the kiln to obtain the combustion optimization control parameters.

8. The method of claim 7, wherein, According to the adjustment strategy, real-time regulate the oxygen supply amount and air distribution system parameters of the burner, and monitor the nitrogen oxide and sulfide emission concentration, including: Obtain the oxygen supply amount and air distribution ratio adjustment strategy from the combustion optimization control parameters and convert them into adjustment instructions; Based on the adjustment instructions, real-time adjust the oxygen supply amount of each burner and synchronously correct the air distribution system parameters; After the execution of the adjusted parameters, real-time collect and analyze the trend of nitrogen oxide and sulfide emission concentration to obtain the emission concentration data. The emission concentration data is compared with the oxygen supply and air distribution adjustment action of the burner to determine whether the emission result meets the target control range; If the emission concentration exceeds the target range, a feedback correction mechanism is triggered to dynamically adjust the oxygen supply and air distribution parameters of the burner until the target control range is met.

9. An optimized control system for cement kiln exhaust emission, for implementing an optimized control method for cement kiln exhaust emission according to any one of claims 1-8, characterized in that, The system comprises: A collection module, which is arranged with oxygen concentration sensors and temperature sensors in multiple key areas inside the cement kiln, collects real-time multi-point oxygen concentration data and combustion temperature data, and generates oxygen concentration change trends for each area in a future period of time in combination with a prediction model; A prediction module, which predicts the temperature distribution trend in the kiln in a future period of time based on the oxygen concentration change trend and the combustion temperature data using a filtering algorithm, determines whether there is a local high-temperature area, and if so, determines the key airflow path in the kiln according to the temperature distribution trend; A state analysis module, which identifies airflow stagnation area position information based on the key airflow path, obtains airflow organization state analysis results, establishes a combustion chemical reaction model according to the state analysis results, determines the sulfide generation trend, and determines the combustion atmosphere regulation and control parameters; An adjustment module, which processes the regulation and control parameters using a control algorithm, determines the optimal oxygen supply and air distribution proportion adjustment strategy, adjusts the oxygen supply and air distribution system parameters of the burner in real time according to the adjustment strategy, monitors the nitrogen oxide and sulfide emission concentration, and dynamically corrects the oxygen supply and air distribution parameters through a closed-loop feedback mechanism.

10. A computer-readable storage medium having stored thereon instructions, the instructions comprising, The instructions are executed by the processor to implement the optimization control method for cement kiln exhaust emission according to any one of claims 1-8.

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